method of inspecting a semiconductor device and an apparatus thereof

ABSTRACT

A method and apparatus of inspecting a sample, in which the sample is inspected under a plurality of inspection conditions, and inspection data obtained by inspecting the sample under each of the plurality of inspection conditions and position information on the sample of the inspection date in correspondence with the respective inspection conditions, are stored. The inspection data for each of the plurality of inspection conditions is against each other by the use of the position information on the sample to determine a position to be inspected in detail, and an image of the sample at a position to be inspected in detail is obtained. The obtained image is classified, the inspection condition of the sample by the use of information of classification of the image is determined.

CROSS REFERENCE TO RELATED APPLICATION

This application is a continuation of U.S. application Ser. No.11/443,222, filed May 31, 2006, which is a Continuation of U.S.application Ser. No. 11/117,336, filed Apr. 29, 2005, Now U.S. Pat. No.7,061,602, which is a continuation of U.S. application Ser. No.09/791,682, filed Feb. 26, 2001, now U.S. Pat. No. 6,888,959, thecontents of which are incorporated herein by reference.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to a method of inspecting a semiconductordevice by which an inspection can be performed under proper inspectionconditions on a semiconductor substrate manufactured in a desiredmanufacturing process of a semiconductor device and an apparatus thereofand, more particularly, to a method of finding an inspection conditionin an inspection apparatus, by which a proper inspection condition isselected to a sample to be inspected and a method of selecting aninspection apparatus to a sample to be inspected.

2. Description of the Related Art

An inspection condition in an inspection apparatus have beenconventionally determined by the steps: inspecting a sample forcalibration, which has bumps and dips equivalent to actual foreignparticles and defects, under a certain inspection condition; analyzingthe state of detection of the bumps and dips; in the case where theresults of the analysis are not good, inspecting the sample forcalibration again under a changed inspection conditions; and theinspection of the sample and analyzing the state of detection of thebumps and dips; and repeating these procedures under differentinspection conditions until the results of analysis become satisfactory.In this way, a proper inspection condition 1 is set.

Here, in Japanese Unexamined Patent Publication No. 9-306957 (relatedart 1) is disclosed a technology for making an identity judgment on aforeign substance in a plurality of processes of a semiconductor wafer.

Also, in Japanese Unexamined Patent Publication No. 4-106460 (relatedart 2) is disclosed a defect detecting technology for calculating thequantity of feature of the same image to be inspected by two differentkinds of parameters, identifying objective defects, detecting defectsidentified in common by two kinds of parameters to thereby eliminate theduplication of detection of the defects.

In this connection, since a circuit pattern formed on a semiconductordevice is becoming more microscopic, foreign particles, circuit patterndefects, and scratches which are required to be detected by inspectionare growing more microscopic.

Further, a semiconductor is manufactured through a very large number ofmanufacturing processes. Therefore, an inspection apparatus needs to beapplied to a semiconductor wafer manufactured through variousmanufacturing processes. However, the condition of the surface(underlying layer) of the semiconductor wafer manufactured throughvarious manufacturing processes varies variously. In this manner, theinspection apparatus needs to detect particles to be detected such asforeign particles, circuit pattern defects, and the scratches, which aregrowing more microscopic, from the variously changing surface of thesemiconductor wafer. Therefore, it is necessary to optimize subtleinspection conditions.

However, it is difficult to form bumps and dips equivalent to foreignparticles and defects on the surface having variously changingconditions as a test sample for calibration and hence theabove-mentioned related arts have a problem that it is difficult to seta proper inspection condition by the use of a test sample forcalibration.

SUMMARY OF THE INVENTION

The present invention provides an inspection method for solving theabove-mentioned problem and capable of inspecting particles to bedetected, such as foreign particles, in accordance with the condition ofthe surface of a sample to be inspected which is manufactured in variousmanufacturing processes, and an apparatus thereof.

That is, the present invention provides a method of inspecting a sample,the method comprising the steps of: inspecting the sample under aplurality of inspection conditions; storing inspection data obtained byinspecting the sample under each of the plurality of inspectionconditions and the position information on the sample of the inspectiondate in correspondence with the respective inspection conditions;checking the inspection data for each of the plurality of inspectionconditions against each other by the use of the position information onthe sample to determine a position to be inspected in detail; obtainingthe image of the position to be inspected in detail; classifying theobtained image; and determining the inspection condition of the sampleby the use of the information of classification of the image.

Further, the present invention provides a method of inspecting a sample,the method comprising the steps of: inspecting the sample under aplurality of inspection conditions; storing inspection data obtained byinspecting the sample under each of the plurality of inspectionconditions and the position information on the sample of the inspectiondate in correspondence with the respective inspection conditions;checking the inspection data for each of the plurality of inspectionconditions against each other by the use of the position information ofthe inspection date on the sample to determine a position to beinspected in detail; obtaining the image of the position to be inspectedin detail; classifying the obtained image; making a group of inspectiondata by the use of the information of classification of the image andthe inspection condition corresponding to the image, and displaying thegroup of inspection data on a screen; and determining the inspectioncondition of the sample out of the group of inspection data displayed onthe screen.

Still further, the present invention provides a method of inspecting asample, the method comprising the steps of: inspecting the sample undera plurality of inspection conditions and storing the information of acandidate for a position to be observed in detail under each of theplurality of inspection conditions; determining a position to beinspected in detail out of the stored information of the candidate forthe position to be inspected in detail under each of the plurality ofinspection conditions; obtaining the image of the position to beinspected in detail; determining the inspection condition of the sampleby the use of the obtained information of the image; and inspecting thesample under the determined inspection condition.

Also, according to the present invention, an apparatus for inspecting asample is constituted by: inspection means for inspecting the sampleunder a set inspection condition; inspection condition setting means forsetting the inspection condition of the inspection means; storage meansfor storing the position data of a candidate to be inspected in detailof the sample, which are obtained by sequentially inspecting the sampleunder a plurality of inspection conditions set by the inspectioncondition setting means with the inspection means, in correspondencewith the data of the plurality of inspection conditions; checking meansfor checking the position data of the candidate to be inspected indetail, which are stored in the storage means, against each other foreach of the plurality of inspection conditions to determine a positionto be inspected in detail; detailed image obtaining means for obtainingthe image of the position to be inspected in detail, which is determinedwith the checking means; image classifying means for classifying theimage obtained with the detailed image obtaining means; and inspectioncondition determining means for determining the inspection condition ofthe sample by the use of the information of the image classified by theimage classifying means.

Also, according to the present invention, an apparatus for inspecting asample is constituted by: inspection means for inspecting the sampleunder a plurality of inspection conditions; storage means for storinginspection data obtained by inspecting the sample under each of theplurality of inspection conditions with the inspection means and theposition information on the sample of the inspection date incorrespondence with the respective inspection conditions; detailedinspection position determining means for checking the inspection data,which are stored in the storage means, for each of the plurality ofinspection conditions against each other by the use of the positioninformation on the sample to determine a position to be inspected indetail; detailed inspection image obtaining means for obtaining theimage of the position to be inspected in detail which is determined withthe detailed inspection position determining means; classification meansfor classifying the image obtained with the detailed inspection imageobtaining means; inspection data making means for making a group ofinspection data by the use of the information of classification of theimage classified with the classification means and the inspectioncondition corresponding to the image, and displaying the group ofinspection date on a screen; and selection means for selecting theinspection condition of the sample out of the group of inspection datadisplayed on the screen with the inspection data making means.

Also, according to the present invention, an apparatus for inspecting asample is constituted by: inspection means for inspecting the sampleunder a plurality of inspection conditions and storing the informationof a candidate of a position to be observed in detail for each of theplurality of inspection conditions; detailed inspection positiondetermining means for determining a position to be inspected in detailout of the candidates of the positions to be inspected in detail, whichare stored in the inspection means, under each of the plurality ofinspection conditions; detailed image obtaining means for obtaining theimage of the position to be inspected in detail which is determined withthe detailed inspection position determining means; and inspectioncondition determining means for determining the inspection condition ofthe sample by the use of the information of the image obtained with thedetailed image obtaining means.

These and other objects, features and advantages of the invention willbe apparent from the following more particular description of preferredembodiments of the invention, as illustrated in the accompanyingdrawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is an illustration of a schematic functional configuration and aschematic processing flow to show one preferred embodiment of aninspection apparatus or a system thereof in accordance with the presentinvention.

FIG. 2 is a schematic block diagram showing an example of an inspectionapparatus A for inspecting foreign particles and the like, in accordancewith the present invention.

FIG. 3 is a schematic block diagram showing an example of an inspectionapparatus B for inspecting defects of a circuit pattern and the like, inaccordance with the present invention.

FIG. 4 is a schematic block diagram showing an example of an inspectionapparatus C for inspecting defects of a circuit pattern and the like, inaccordance with the present invention.

FIG. 5 is a schematic block diagram specifically showing an example ofan inspection apparatus A for inspecting foreign particles and the like,in accordance with the present invention.

FIG. 6 is an illustration to show a first example of a processing flowfor selecting an optimal inspection condition to a sample to beinspected, in accordance with the present invention.

FIG. 7 is an illustration to show a second example of a processing flowfor selecting an optimal inspection condition to a sample to beinspected, in accordance with the present invention.

FIG. 8 is an illustration to show inspection data obtained by inspectinga sample to be inspected under a plurality of inspection conditions.

FIG. 9 is an illustration to show examples of various kinds of dataarbitrarily selected from check data for display in order to facilitatereviewing or analyzing results of inspection.

FIG. 10 is an illustration to show examples of check data displayed bycharacters or numerals.

FIG. 11 is an illustration to show an embodiment in which inspectiondata including the data assigned by classifying a detected substance forthe respective inspection conditions are displayed in the form of alist.

FIG. 12 is an illustration to show the state of checking the inspectiondata obtained under various inspection conditions against each other.

FIG. 13 is an illustration to show the results of analysis of thematerials of foreign particles and the like.

FIG. 14 is an illustration to show an embodiment of a processing flowfor selecting an optimal inspection apparatus out of a plurality ofinspection apparatuses of the same kind or approximately the same kindto a sample to be inspected, in accordance with the present invention.

FIG. 15 is an illustration to show an embodiment of a processing flowfor selecting an optimal inspection apparatus among a plurality ofinspection apparatuses of different kinds to a sample to be inspected,in accordance with the present invention.

FIG. 16 is an illustration to show a first embodiment in which anidentity judgment is performed on a detected substance based on an errorcomponent due to a difference between inspection apparatuses.

FIG. 17 is an illustration to show a second embodiment in which anidentity judgment is performed on a detected substance based on an errorcomponent due to a difference between inspection apparatuses.

FIG. 18 is an illustration to show a third embodiment in which anidentity judgment is performed on a detected substance based on an errorcomponent due to a difference between inspection apparatuses.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

Preferred embodiments of an inspection method and an apparatus thereofin accordance with the present invention will be described withreference to the accompanying drawings.

To begin with, a case where a sample to be inspected is a semiconductorwafer will be described.

Since a semiconductor device is manufactured by many manufacturingprocesses, a semiconductor wafer is different in the material of asurface and the shape of a circuit pattern between the manufacturingprocesses. Also, a foreign substance inspection apparatus or anappearance inspection apparatus is used over a plurality of differentmanufacturing processes, or is provided in each of a plurality ofdifferent manufacturing processes. As a result, the present inventionprovides a method capable of inspecting a semiconductor wafer byadjusting inspection conditions and setting an optimal inspectioncondition for each manufacturing process, and an apparatus thereof.

Also, a foreign substance, a circuit pattern defect, and a flaw like ascratch, which are permissible on a semiconductor wafer, are becomingincreasingly microscopic. For this reason, the present invention isintended to assign a manufacturing process a suitable inspectionapparatus among the inspection apparatuses of the same kind having aslight difference in performance among them. Further, even in the casewhere different kinds of inspection apparatuses are used, they aredifferent in an inspection capacity among them and hence the presentinvention is intended to assign a suitable kind of inspection apparatusto a manufacturing process.

Next, examples of an inspection method and an apparatus thereof inaccordance with the present invention will be described with referenceto FIG. 1.

In a group 10 of a plurality of kinds of inspections, a plurality ofkinds of inspections are performed on foreign particles and defects (forexample, microscopic uneven defects including defects of a circuitpattern, defects, and the like) on a sample to be inspected 1 such assemiconductor wafer. This group 10 of inspections includes the followinginspection processes: (a) inspections are performed on the sample undera plurality of different inspection conditions of illuminatingcondition, detecting condition, image processing condition (condition ofinspection algorithm), and the like by the use of the same inspectionapparatus; (b) inspections are performed on the sample by the use of aplurality of inspection apparatuses of the same kind or approximatelythe same kind; (c) inspections are performed on the sample by the use ofinspection apparatuses of different kinds (for example, an opticalinspection apparatus shown in FIG. 2, an optical inspection apparatusshown in FIG. 3, an optical inspection apparatus shown in FIG. 4, or aSEM appearance inspection apparatus).

A group of inspection data 11 is obtained as a set as the results ofinspections from the respective inspections in the group 10 of pluralkinds of inspections performed on a sample to be inspected having asurface condition made by a certain manufacturing process.

Further, in a CPU 20, an identity judgment processing (check processing)30 is performed on the group of inspection data 11 obtained by theplural kinds of inspections conducted in the group 10 of inspections,and the results of the identity judgment processing 30 (results of thecheck processing) are taken out as data 31 after the identity judgmentprocessing (results of the check processing), and an analysis processing40 is performed on the data. In this manner, the identity judgmentprocessing 30 performed on the group of inspection data 11 largelydecreases the number of detected particles in the data 31 after theidentity judgment processing 30 by the number of data judged to beidentical. In the analysis processing 40, the detected particles,largely decreased in number, are analyzed (reviewed) in detail byvarious kinds of analysis processes and are classified by category (forexample, foreign substance, false information, circuit pattern defect,scratch (flaw), and the like) to produce a group 41 of analysis data.Naturally, sensitivity (size of foreign substance, circuit patterndefect and scratch) is also included in the category of classificationand, for example, the sensitivity of the foreign substance includes adetection capability of 0.1 μm, 0.2 μm, and 0.5 μm.

In an analysis data compiling 50, the information of the group 41 ofanalysis data (classification of detected particles by category)obtained by the analysis processing 40 is fed back to the group ofinspection data 11 and the results thereof can be stored as a singleunit in a storage device 60 as inspection data 51 and also displayed ona display device 61. That is, in the analysis data compiling 50, byfeeding back the information of the group 41 of analysis data(classification of detected particles by category) to the data obtainedfrom the group of inspection data 11, a group of inspection data 51 acan be produced as the inspection data 51, for example, a group 51 a ofinspection data shown in FIG. 5.

By displaying the group 51 a of inspection data, for example, on thedisplay device unit 61, an operator can select, on a display screen, anoptimal inspection condition for the sample 1 to be inspected among thegroup 10 of plural kinds of inspections and can set the selectedinspection condition for an inspection apparatus. As a result, theinspection apparatus can perform an inspection on the sample 1 to beinspected under the set optimal inspection condition.

As described above, according to the present invention, the group 10 ofplural kinds of inspections are performed on the sample to be inspectedwhich has a certain surface condition manufactured by a givenmanufacturing process to produce, in a single unit, the group 11 ofinspection data as the results of the respective inspections; and theidentity judgment processing (check processing) 30 is preformed on theseproduced group 11 of inspection data to produce the data 31 to reducethe number of detected particles on which the analysis processing(reviewing) 40 is performed; and the analysis processing (reviewing) 40is performed on the reduced number of detected particles to classify thedetected particles by category or kind; and the classified kinds of thedetected particles are fed back to the group 11 of inspection data. Inthis way, the operator can select an optimal inspection condition amongthe plural kinds of inspections and set the optimal condition to theinspection apparatus with efficiency in a short time. Of course, it ispossible to instantaneously recognize the distribution of the detectedparticles on the sample to be inspected by displaying the data after theidentity judgment processing.

As an example of an inspection apparatus A for inspecting a foreignsubstance, there is provided an apparatus having a configuration shownin FIG. 2. That is, the apparatus is composed of: a stage 101 for havinga sample 1 to be inspected 1 placed thereon and measuring itsdisplacement coordinates; a stage moving section 102 a for moving thestage 101; a stage control section 103 a for controlling the stagemoving section 102 a based on the displacement coordinates of the stage101 measured by the stage 101; an obliquely illuminating optical system104 for obliquely illuminating the sample 1 to be inspected, which isplaced on the stage 101; a detecting optical system 107 including acollective lens 105 for collecting scattering light (diffracted light oflow order other than 0 order) from the surface of the sample 1 to beinspected and a photoelectric transducer 106 composed of a TDI, a CCDsensor or the like; an illumination control section 108 for controllingthe quantity of illuminance and the angle of irradiation when light fromthe obliquely illuminating optical system 104 illuminates the sample 1to be inspected; a judgment circuit (inspection algorithm circuit) 109 awhich aligns an inspection image signal produced by the photoelectrictransducer 106 with a standard image signal (reference image signal)produced by a neighboring chip or cell, and compares them to extract adifferential image from both the image signals, and judges the extracteddifferential image by a previously predetermined threshold to detect animage signal indicating a foreign substance to judge the foreignsubstance or, if necessary, further calculates the quantity of features(area, length, center of gravity, and the like) of the detected imagesignal indicating the foreign substance to judge the foreign substance;a CPU 110 a for performing various kinds of processes on the foreignsubstance judged by the judgment circuit 109 a based on the stagecoordinate system obtained by the stage control section 103 a; aninput/output device 111 a (key board, mouse, recording media, or thelike) connected to the CPU 110 a; a display device 112 a; and a storagedevice 113 a for storing various kinds of inspection data processed bythe CPU 110 a.

The above-mentioned inspection apparatus A detects scattering light(diffracted light of low order), which is generated by a foreignsubstance existing on the sample 1 to be inspected when light isobliquely applied to the sample 1 to be inspected by the obliquelyilluminating optical system 104, by the detecting optical system 107.

The photoelectric transducer 106 can receive only scattering lightgenerated by a foreign substance by shielding a diffracted light patterngenerated by the repetition pattern of a memory cell or the like on thesample 1 to be inspected by the use of a spatial filter 105 a shown inFIG. 5. Here, the CPU 110 a may be connected to a server 115 storing theinspection data or a terminal 120 via a network 114. Further, in theinspection apparatus A, as shown in FIG. 5, it is required to previouslyinput a plurality of inspection conditions Ta, Tb, Tc, . . . from aninput device 111 a and to store them as a group of inspection data 300a. Still further, in the inspection apparatus A, as shown in FIG. 5, itis necessary to store in the storage device 113 a a group 11 a ofinspection data, which is the results of inspection obtained from theCPU 110 a under a plurality inspection conditions Ta, Tb, Tc, . . .

Further, also in the inspection apparatus A for inspecting a foreignsubstance, it is possible to discriminate a foreign substance from ascratch (flaw) based on the difference between the foreign substance andthe scratch by calculating the quantity of feature of the defectdetected by the judgment circuit 109 a.

Still further, in the inspection apparatus A for inspecting a foreignsubstance, it is also recommended that a polarizing laser be obliquelyapplied to the sample 1 to be inspected, and that scattering light,generated by the edge of a circuit pattern formed on the sample 1 to beinspected, be shielded by means of an analyzer, and that scatteringlight generated by a foreign substance be made to pass through theanalyzer and be detected by the photoelectric transducer 106.

An inspection apparatus B shown in FIG. 3 is the one used for inspectingmicroscopic uneven defects and defects in a circuit pattern and providedwith a vertical illuminating optical system 124, which is composed of alight source 121 for vertical illumination, a collective lens 122, and amirror 123 b such as a small mirror, a half mirror, a polarization beamsplitter, and the like, and a detecting optical system 128 b composed ofan objective lens 125 b, an image forming lens 126 b, and aphotoelectric transducer 127 b.

In the case where the polarization beam splitter 123 b is used, it isrecommended that a light source to emit a polarizing laser beam be usedas the light source 121, and that illumination light circularlypolarized with a λ/4 plate interposed between a polarization beamsplitter, which is the mirror 123 b, and the objective lens 125 b beapplied to the sample 1 to be inspected, and that scattering lightproduced by the defects is transmitted through the polarization beamsplitter which is the mirror 123 b.

In any case, it is desirable also in the inspection apparatus B that thespecular reflection light from the surface of the sample 1 to beinspected, caused by vertical illumination, is shielded, for example, bya spatial filter or the like, to prevent the photoelectric transducer127 b from receiving the specular reflection light, and that thephotoelectric transducer 127 b receives scattering light generated bythe above-mentioned defects. That is, the configuration, other than theilluminating optical system 124, of the inspection apparatus issubstantially constituted in the same way as the inspection apparatus A.

A judgment circuit 109 b aligns an inspection image signal which isproduced by the photoelectric transducer 127 b, which receives anoptical image of a circuit pattern formed by an image forming lens 126b, with a standard image signal (reference image signal) produced by aneighboring chip or cell, and compares the inspection image signal andthe standard image signal, which are aligned with each other, to extracta differential image from both the image signals, and judges theextracted differential image by a previously set predetermined thresholdto detect an image signal indicating a circuit pattern defect, andjudges the circuit pattern defect based on the detected image signalindicating a foreign substance or, if necessary, further calculates thequantity of features (area, length, center of gravity, and the like) ofthe detected image signal indicating the circuit pattern defect andjudges the circuit pattern defect based on the calculated quantity offeatures.

Also, an inspection apparatus C, as shown in FIG. 4, is provided withboth of the obliquely illustrating optical system 104 shown in theinspection apparatus A in FIG. 2 and the vertical illuminating opticalsystem 124 shown in the inspection apparatus B in FIG. 3, and adetecting optical system 128 c having approximately the sameconfiguration as, for example, the detecting optical system 128 b shownin FIG. 3. In this manner, since the inspection apparatus C is providedwith both of the illuminating optical systems, if the respective opticalsystems are alternately applied light to the sample 101 to be inspected,respectively, then the photoelectric transducer 127 c receives differentoptical images formed by the respective illuminations, which makes itpossible to discriminate between a foreign substance and a circuitdefect and hence to inspect them with high sensitivity. Naturally, it isnecessary to change an inspection algorithm in the judgment circuit 109c between the judgment of the foreign substance and the judgment of thecircuit pattern defect. Also, this configuration makes it possible todiscriminate the foreign substance and the circuit pattern defect fromscratches of microscopic dips in the inspection by comparing theintensity signals of the scattering light obtained from thephotoelectric transducer 127 c by the respective optical systems and bycalculating a ratio of the intensity signals.

In addition to this, as still another inspection apparatus, there isprovided an appearance inspection apparatus using a SEM (SecondaryElectron Microscope).

Here, in the inspection apparatus A, as shown in FIG. 5, it is necessaryto previously input a plurality of inspection conditions Ta, Tb, Tc, . .. by the use of an input device 111 a and to store them in a storagedevice 113 a as a group 200 a of inspection conditions. Also, a group300 a of inspection data under the plurality of inspection conditionsTa, Tb, Tc, . . . , which is obtained from a CPU 110 a is stored in thememory device 113 a.

Here, also in the inspection apparatus B or C, as is the case with theinspection apparatus A shown in FIG. 5, it is necessary to previouslyinput a plurality of inspection conditions Ta, Tb, Tc, . . . by the useof an input device 111 b or 111 c and to store them in a storage device113 b or 113 c as a group 200 b or 200 c of inspection conditions. Also,in the inspection apparatus B or C, as is the case with the inspectionapparatus A shown in FIG. 5, a group 300 a of inspection data under theplurality of inspection conditions Ta, Tb, Tc, . . . , which is obtainedfrom a CPU 110 b or 110 c, is stored in a memory device 113 b or 113 c.

Next, a group 10 of plural kinds of inspections with respect to thesample 1 to be inspected will be described in detail.

The plural kinds of inspections mean the plural kinds of inspections dueto a difference in optical conditions such as:

(a) in the inspection using the same inspection apparatus A, B, or C,(a-1) illuminating conditions (for example, in the case of illuminatingoptical systems 104, 124 shown in FIG. 2, FIG. 3 and FIG. 4, among theilluminating conditions is the quantity of illuminating light controlledby an illumination control section 108 a, 108 b, or 108 c; in the casewhere a light source is a laser light source, a laser power emitted fromthe laser light source controlled by the illumination control section108 a, 108 b, or 108 c is one of the illuminating conditions; also, ifthe angle of the oblique illumination can be changed by the illuminationcontrol section 108 b or 108 c in the illuminating optical system 104shown in FIG. 2 or FIG. 4, then the angle of the oblique illumination isincluded in the illuminating conditions; and, in the case where theinspection apparatus is provided with a plurality of illuminatingoptical systems, the switching control of the plurality of illuminatingoptical systems is included in the illuminating conditions); anddetecting conditions (for example, focus controlling conditions—focusoffset and the like), controlling conditions of the phase and pitch of alight shielding pattern in the case of a variable spatial filterdisclosed in Japanese Unexamined Patent Publication No. 6-258239, themoving speed of a stage 101 controlled by the stage control section103); and

(a-2) plural kinds of inspections due to a difference in an inspectionalgorithm (for example, a difference in a judgment parameter such as athreshold map (threshold image) to judge a foreign substance and adefect, and a difference in an alignment accuracy between a detectedimage signal and a standard image signal.

In this connection, in the case where the sample 1 to be inspected is asemiconductor wafer, the detection signal detected by the photoelectrictransducer 106, 107 b, or 107 c has variations due to a subtledifference in the process which does not cause a defect, noises duringthe detection, and the like. That is, signal levels from correspondingpixels between chips formed on the semiconductor wafer are not the samevalues but have variations. To be more specific, the detection signalsare different in variations among regions having different structures inthe circuit pattern (for example, in the case of a memory LSI, a memorycell region, a peripheral circuit region, and the other region).

As a result, in the regions where variations in the detection signal aresmall can be detected a defect causing a small change in the detectionsignal such as a foreign substance and the like, whereas in the regionswhere the variations in the detection signal are large can be detectedonly a defect causing a large change in the detection signal.Accordingly, a threshold which is one of the inspection conditionscorresponds to a value obtained by multiplying a variation (standarddeviation σ) in the detection signal among the corresponding regionsamong the chips by a magnification m. That is, this threshold levelcorresponds to the condition of the underlying layer (repetition patternregion, region with an extremely rough surface, region with a thickfilm, region with a small size pattern, or the like).

Therefore, in the case where a map of various thresholds is prepared asone of the plurality of inspection conditions, if the threshold is low,small defects can be detected, but false information increases, and ifthe threshold is high, only large defects can be detected. As a result,also in the threshold map, there is an optimal condition for theunderlying condition.

Also, in the case where the quantity of light (laser power) is changedas one of the plurality of inspection conditions, if the laser power isincreased, sensitivity is also increased to enable the detection of asmall defect like a small foreign substance but scattering light fromthe underlying layer is also increased to increase the area of thesaturated regions (regions not to be inspected), and if the laser poweris decreased, the sensitivity is also decreased and hence only largedefects can be detected but scattering light from the underlying layeris decreased to extremely decrease the area of the region not to beinspected. Therefore, there is an optimal condition also for the laserpower according to the size of a foreign substance to be detected andthe like and the condition of the underlying layer.

Also, the phase and pitch of the light shielding potion of the spatialfilter are required to meet the structure of the underlying layer of thesample to be inspected.

The plural kinds of inspections fundamentally mean (b) an error(variation) due to the difference between inspection apparatuses in theinspection using a plurality of inspection apparatuses of the same kindor approximately the same kind.

The plural kinds of inspections mean (c) in the inspection usinginspection apparatuses of different kinds, (c-1) plural kinds ofinspections due to a difference in optical conditions such asilluminating conditions (for example, method of applying an illuminatingbeam to the sample 1 to be inspected based on a difference in the lightsource such as laser, white light, electron beam, ion beam, x-ray, orthe like, wavelength of illuminating light, direction of illumination,angle of illumination, and a combination of a plurality ofilluminations) and detecting conditions (for example, a difference inthe kind of detector such as a CCD sensor, a TDI sensor, an X-raydetector, a secondary electron detector, a photomultiplier, a secondaryion detector, and a difference in detecting optical system), and (c-2)the plural kinds of inspections due to a difference in an imageprocessing algorithm with respect to the image signal obtained fromvarious kinds of optical conditions.

Next, (a) a first preferred embodiment in accordance with the presentinvention for setting an optimal inspection condition will be describedusing FIG. 6 to FIG. 8 in which a plurality of inspections is performedas a single unit under a plurality of different inspection conditions bythe use of the same inspection apparatus. FIG. 6 and FIG. 8 show thecases where the inspection apparatus A shown in FIG. 2 can inspectforeign particles and scratches (defects), and FIG. 7 show the casewhere the inspection apparatus A can inspect only foreign particles.

The inspection conditions, as described above, include the ones relatedto adjustable, controllable factors of the illuminating optical systemsuch as quantity of illumination, polarization of illuminating light,and direction of illumination; the ones related to the adjustable,controllable factors of the detecting optical such as the phase andpitch of light shielding pattern of the spatial filter, and parametersto be changed in setting (for example, threshold map) of the inspectionalgorithm, and these inspection conditions can be set and stored in thestorage device 113 a by the use of the input device 111 a. Naturally,the CPU 11 a has a function to control the whole inspection apparatusand controls the illumination control section 108 a, the stage controlsection 103 a, the judgment circuit 109 a, and the spatial filter 105 asuch that the sample 1 to be inspection can be inspected based on theset inspection conditions Ta, Tb, Tc, . . . .

First, in the case of the inspection apparatus A capable of inspecting aforeign substance and the like with excellent sensitivity, as shown inFIG. 2 and FIG. 5, when the same sample 1 to be inspected, which ismanufactured in the manufacturing process to be inspected, is inspectedas a single unit with the inspection apparatus A under a plurality ofinspection conditions Ta, Tb, Tc, . . . stored in the storage device 113a, as shown in FIG. 6 to FIG. 8, a group 11 a of inspection data DaTa,DaTb, DaTc, . . . , which are the results of the inspections under therespective inspection conditions, can be obtained, with respect tocoordinates set for the sample 1 to be inspected and are stored in thestorage device 113 by the judgment circuit 109 and the CPU 110 a.

As the inspection data, not only the coordinates of detected particlesbut also the quantity of features of the respective detected particlesor the brightness image signals of the detected particles, which areobtained from the judgment circuit 109, are stored as correspondingpairs so that they can be reviewed or analyzed and classified. Here, theerror between the stage coordinates obtained by the stage controlsection 103 and the coordinates set on the sample 1 to be inspected canbe corrected in the CPU 110 a by detecting the reference mark formed onthe sample 1 to be inspected.

Next, the CPU 110 a compares the coordinates of the detected particlesof a plurality of inspection data obtained under the respectiveinspection conditions to judge the identity of the positions of thedetected particles and checks the plurality of inspection data based onthe identity judgment and stores the data 31 a of the results of check(data after the identity judgment) in an internal memory (not shown) orthe storage device 113.

In this connection, in the case of the present preferred embodiment,only the inspection conditions are changed and hence, basically, it isessential for the judgment of identity only that alignment errors basedon the stage control of the sample 1 to be inspected and detectionerrors caused according to size of the detected substance and theintensity of the signal detected from the detected substance are takeninto account. Therefore, when the spacing between the detected particlesdetected under the respective inspection conditions is smaller than twotimes the above-mentioned alignment error, it is recommended that thedetected particles be judged to be the same substance.

That is, when detection regions are set two-dimensionally according tothe alignment error around the positions of the detected particlesdetected under the respective inspection conditions and the setdetection regions overlap each other, the detected particles may bejudged to be the same substance. As described above, by performing anidentity judgment on the plurality of inspection data inspected andobtained as a single unit under the plurality of inspection conditions,the number of detected particles to be analyzed can be decreased, whichis described below, and by outputting the data after the identityjudgment, the distribution of the detected particles can be recognizedinstantaneously.

Next, the CPU 110 a displays the data 31 a of check results stored inthe storage device 113 and the quantity of feature or the brightnessimage signal of the detected substance on the display device 112 in theanalysis processing section (step) 40. A category (foreign substance,false information, scratch (flaw)) including a size is assigned by theinput device 111 to each detected substance, based on the quantity offeature and the brightness image signal of the detected substance, whichare displayed on the display device 112, to thereby produce theclassified review result (analysis data) 41 a of the detected substance.The classified review result 41 a and coordinates of the detectedsubstance are stored in the internal memory or the storage device 113.Here, the size of the detected substance can be assigned by determiningthe area of the image signal indicating the detected substance. Also,the CPU 110 a may automatically classify each detected substance by thequantity of feature thereof by means of ADC (automatic defectclassification) and may automatically assign a category to the detectedsubstance. This ADC is provided as an additional function of theinspection apparatus or as a dedicated automatic review device.

In this connection, as a method of displaying the data 31 a of checkresults, when the inspection data DaTa, DaTb under the inspectionconditions shown in FIG. 8 are obtained, various methods shown in FIG. 9and FIG. 10 are proposed so as to facilitate reviewing or analyzing thedata. That is, FIG. 9( a) shows the logical OR data 81 of both of theinspection data DaTa, DaTb, FIG. 9( b) shows the identity data 82 ofboth of the inspection data DaTa, DaTb, FIG. 9( c) shows thenon-identity data 83 of both of the inspection data DaTa, DaTb, FIG. 9(d) shows the data 84 of both of the inspection data DaTa, and FIG. 9( d)shows the data 85 only under the inspection condition Tb.

In FIG. 10( a), the inspection data are displayed with their inspectionconditions distinguished from each other, and in FIG. 10( b), there aredisplayed the number of detections of the detected particles when theinspections are performed on them under different inspection conditions.By selecting various types of displays for the data 31 a of checkresults, the data 31 of check results can be checked against theinspection conditions, whereby the detected particles can be easilyclassified into the above-mentioned categories.

The selection of the various types of displays includes: (1) selectionof the logic OR data 81; (2) as for the identity data 82, selection ofthe data having a low possibility of being false information, orselection of the non-identity data 83 as the detected substance whichresists appearing even if the inspection conditions are changed; (3)selection of the data obtained by adding the identity data 82 to thenon-identity data 83 in (2) at an arbitrary ratio, (4) selection of thedata of the number of detections smaller than an arbitrary number ofdetections out of the data of the number of detections of the detectedparticles under the plurality of inspection conditions; (5) selection ofdata obtained by specifying the region on the sample to be inspectedwith respect to the respective data in the above-mentioned (1) to (4);(6) selection of the data extracted at an arbitrary ratio from therespective data in the above-mentioned (1) to (4); and (7) selection ofa combination of the above-mentioned (5) and (6).

By selecting these various types of displays and displaying them on thedisplay device 112, the state where the detected particles are detectedfrom the surface of the sample to be inspected can be grasped tofacilitate analyzing the detected particles, that is, classifying theminto the categories. For example, as for the false information, there islittle possibility that it is detected as identity data and hence theselection of the data in (2) may be meaningful. Also, since the falseinformation is small in the number of detections and the substance newlydetected under a given inspection condition (whose category isdetermined in some case by the given inspection condition) is small inthe number of detections, the selection of the data in (4) ismeaningful. Further, as described above, since the detection of thedefects is largely affected by the underlying region of the sample to beinspected (including a peripheral region, a central region, and a regionin a chip), the selection of the data in (5) is meaningful. Stillfurther, when the inspection conditions do not become suitable, manydetected particles are produced on the sample to be inspected. Hence, ifthey are checked against each other and the checking results areoutputted on the display at a time, then the analysis of the checkingresults is very difficult. Therefore, in order to display a part of thedefected particles, the selection of the data in (6) is necessary.

Next, the CPU 110 a feeds back the analysis data (review results) 41 awith categories assigned thereto to the group of inspection data 11 a toform a group 51 a of inspection data KaTa, KaTb, KaTc, . . . , which areclassified by the inspection conditions, for example, in an analysisdata compiling section (step) 50 and stores them in the storage device113. Then, the CPU 110 a displays the stored group of inspection data 51a, for example, to the display device 112 to inform an operator that aninspection condition Tb is an optimal inspection condition under whichfalse information is little included and foreign particles and the likecan be detected, which results in enabling the operator to select andset the optimal inspection condition Tb with respect to the sample 1 tobe inspected to the above-mentioned inspection apparatus A by the use ofthe input device 111. Therefore, after the optimal inspection conditionis selected and set to the inspection apparatus A, the inspectionapparatus A can inspect the sample 1 to be inspected, manufactured in agiven manufacturing process, under the inspection condition mostsuitable to the surface condition of the sample 1 to be inspected.

In this connection, various types of displays such as map, list, or thelike are thought as the methods of displaying the group of inspectiondata 51 a including the plurality of inspection data Ka on the displaydevice 112. In FIG. 11, there is shown the form of list in whichinspection conditions are described. As is clear from this form of list,the inspection conditions B and C have little false information andhence can be selected as optimal inspection conditions on the screen ofthe display device 112 by the use of the input device 111. Also, sincethreshold images/histograms are displayed on the screen, it is possibleto judge whether the threshold is proper or not. Also, the inspectiondata can be displayed by means of Venn map shown in FIG. 12. Also, theinspection data K of the respective inspection conditions can bediscriminated by a character, a symbol, a numeral, a figure, a color ora size, as shown in FIG. 10, as is the case with the display of the data31 a of check results.

Further, by analyzing the sample to be inspected, which is reviewed andclassified, by means of a mass spectrometer or an X-ray spectrometer,the material of the foreign substance is analyzed into Al, Si, Cu, andunknown. Then, by inputting this data into the CPU 110(20), the materialof the foreign substance can be displayed on the display device 112 andthe category of the foreign substance can be determined with reliabilityand the cause of generation of the foreign substance can be trackeddown.

As described above, according to the above-mentioned preferredembodiments, if a sample 1 to be inspected, manufactured by a givenmanufacturing process, is inspected in a single unit under a pluralityof inspection conditions with an inspection apparatus and detectedparticles are checked against each other, the detected particles can bereviewed and classified at a time. As a result, time required todetermine an optimal inspection condition can be largely shortened.

Next, (b) an inspection of a preferred embodiment in accordance with thepresent invention in the case where the inspection is performed on asample to be inspected with a plurality of inspection apparatuses of thesame kind or approximately the same kind will be described withreference to FIG. 14.

In the present preferred embodiment, the CPU 20 constituting an identityjudgment processing section (step) 30, an analysis processing section(step) 40, and an analysis data compiling section (step) 50 may beconnected to each of a plurality of inspection apparatuses through anetwork, or may be composed of a CPU 110 which is built in each of theplurality of inspection apparatuses. In the latter case, however, theCPUs 110 built in the plurality of inspection apparatuses are connectedto each other through a network. Also, to the above-mentioned CPU 20 areconnected an input device 111, a display device 112, and a storagedevice 113.

In the case of this preferred embodiment, as shown in FIG. 14, the samesample 1 to be inspected, manufactured in given manufacturing process,is inspected by the inspection apparatus A and the inspection apparatusA′, both of which are of the same kind or approximately the same kind,under the same inspection condition Ta and inspection data DaTa, Da′Tacan be obtained. The CPU 20 (110) performs an identity judgment on thedetected substance in the state where error components caused by theapparatus difference between the inspection apparatus A and theinspection apparatus A′ are added to the inspection data DaTa, Da′Ta toproduce the data 31 b of check results. The above-mentioned errorcomponents include, for example, an error caused by the accuracy of thetransfer mechanism of the stage 101 and the like, a detection errorcaused by, for example, a rotary encoder or a linear encoder fordetecting the displacement of the stage 101, a conversion error in thecase where coordinates are different between the respective inspectiondata, an assembly error of the inspection apparatus itself, and apositioning error caused by a misalignment caused when the sample 1 tobe inspected is mounted on the respective inspection apparatuses A, A′.

The subsequent procedures of processing the inspection data are the sameas those of the preferred embodiment shown in FIG. 5, FIG. 6, and FIG.7. Here, review results (analysis data) 41 b are the review resultsbased on the data 31 b of check results. In this manner, furtherdetailed investigation based on the group of inspection data 51 bobtained for the respective inspection apparatuses enables an apparatusanalysis of the inspection apparatuses of the same kind or approximatelythe same kind.

As a result, it is possible to select the inspection apparatuses A, A′suitable for the sample 1 to be inspected, manufactured in a givenmanufacturing process, from the inspection data KaTa, Ka′Ta (51 b)obtained for the respective inspection apparatuses. In the case of thepreferred embodiment shown in FIG. 14, since the inspection apparatus A′can comparatively well detect foreign particles and scratches, theinspection apparatus A′ comes to be selected. Here, at this time, bychanging the inspection conditions in the same way for the respectiveinspection apparatuses A, A′, the inspection accuracy can be improved toa suitable extent.

Next, (c) an inspection in accordance with the present invention in thepreferred embodiment in which the inspection is performed withinspection apparatuses of different kinds will be described withreference to FIG. 15. Also in this preferred embodiment, the CPU 20 iscomposed in the same manner as the preferred embodiment in (b). As shownin FIG. 15, the sample 1 to be inspected, manufactured in a givenmanufacturing process, are inspected by an inspection apparatus A and aninspection apparatus B, which are different in kind from each other,under the same inspection condition Ta, and inspection data DaTa, DbTacan be obtained. A CPU 20 (110) makes an identity judgment on a detectedsubstance in the state where an error component caused by the apparatusdifference between the inspection apparatus A and the inspectionapparatus B, which are different in kind from each other, is added tothe inspection data DaTa, DbTa in an identity judgment processing (step)30 to thereby produce the data 31 c of check results.

In the case of this preferred embodiment, the error component is set foreach kind of the inspection apparatus. That is, the CPUs 110 of therespective inspection apparatuses A, B obtain inspection data indicatingabnormalities such as a foreign substance, a defect, and the like from ajudgment circuit 109 and determine coordinate data indicating theposition information of the detection data based on a stage coordinatesystem given by a stage control section 103 and store them in a storagedevice 113. Therefore, for example, the identity judgment processingsection 30 of the CPU 20 makes one arbitrary coordinate data amongcoordinate data indicating position information of the detectedparticles of the inspection data obtained from the CPUs 110 of two ormore arbitrary inspection apparatuses, out of the group of inspectiondata 11 obtained from the CPUs 110 of the respective inspectionapparatuses and shown in FIG. 1, standard coordinate data, and comparesthe standard coordinate data and the remaining other coordinate data tomake an identity judgment on the detected particles. Here, the identityjudgment processing section 30 makes the identity judgment on thedetected particles based on the above-mentioned apparatus errorcomponents Z1, Z2 of the respective inspection apparatuses.

Here, it is thought that the accuracy of coordinates of the inspectiondata used for the identity judgment are largely different from eachother because of the size of the detected substance, the intensity ofsignal of the detected substance, and the kind of the inspectionapparatus. Also, as the methods for making the identity judgment, thereare various methods as shown in FIG. 16 to FIG. 18. Each of them showsin one coordinate system the respective coordinate data indicatingcoordinates of the substance detected by the inspection apparatus A andthe inspection apparatus B. Reference characters a1, a2 designate theparticles detected by the inspection apparatus A and referencecharacters b1, b2 designate the particles detected by the inspectionapparatus B. Reference characters 91, 92 designate the regions of thedetected particles a1, b1. Reference characters 93, 94 designate theregions of the detected particles a2, b2. Each of the detection regions91, 92 is constituted by a square whose center is the point havingcoordinates of the detected substance a1 or b1 and whose side is twotimes the detection error component Z1 of the inspection apparatus Aitself. Each of the detection regions 93, 94 is constituted by a squarewhose center is the point having coordinates of the detected substancea2 or b2 and whose side is two times the detection error component Z2 ofthe inspection apparatus B itself. Identity judgment of the detectedparticles is made according to whether the detection regions of therespective detected particles overlap each other. Since the detectionregions 91, 92 of the detected particles a1, b1 overlap each other, thedetected particles a1, b1 are judged to be identical. Since thedetection regions of the detected particles a1 and b2, a2 and b1, and a2and b2 do not overlap each other, the respective detected particles a1and b2, a2 and b1, and a2 and b2 are judged not to be identical. The useof this method enables more unerring identity judgment.

In addition to the above method, there is proposed, for example, amethod in which each of the detection regions, as shown in FIG. 17, iscomposed of a circle having a center at the point having coordinates ofeach detected substance and a radius of the detection error Z1 or Z2, amethod in which the detection region is applied to one detection data,as shown in FIG. 18, or a combination of these methods.

As described above, by displaying the data 31 c of the checking resultsobtained from the identity judgment on the display device 112, it ispossible to instantaneously recognize how the particles detected by theinspection apparatuses A, B are distributed. Also, when a detailedanalysis is made, it is possible to analyze the inspection data DaTa,DbTa produced by the inspection apparatuses A, B as a single unit,instead of analyzing them separately.

When the inspection apparatuses are different from each other, it isthought that the kinds and the number of items of the data stored withrespect to the detected particles such as the form of file, the methodof determining coordinate axes, the accuracy of coordinates, and thelike may be different in the group 11 of inspection data between theinspection apparatuses. In view of these, it is desirable that the data31 c after the identity judgment, which are the results of checking, canrespond to all the kinds and the number of items of the data that can bethought as the group 11 of inspection data. In the identity judgmentprocessing section 30, the data 31 c after the identity judgment needsto store the results of the identity judgment with respect to at leastthe group 11 of inspection data, and desirably further has the followingconditions: the data 31 c after the identity judgment are in the form offile that can be used by the analysis processing section 40, or can beconverted into the form of file to be used by the analysis processingsection 40, and can be fed back to the original group 11 of inspectiondata. At this time, the display examples shown as those of the dataafter the identity judgment need to be arbitrarily selected and beconverted into files.

Next, a method of arbitrarily selecting objects to be inspected when theanalysis processing section 40 reviews or analyzes them and makes adetailed inspection, such as classification, on them and an apparatusthereof will be described.

The data processing method used by the analysis processing sectionincludes: a method of writing the respective data, shown in the displayexample of the data 31 c after the identity judgment, to a file for use;a method of selecting the respective data out of the respective data atrandom in the arbitrarily determined proportions; a method of specifyingthe above-mentioned detection region on the display screen or by thecoordinate and selecting the data in the detection region; a method ofdirectly selecting the data displayed in the form of a map or a list;and a combination of these selecting methods.

Next, the method of reviewing, analyzing, and classifying the data willbe described in detail.

That is, the analysis processing section 40 reviews or analyzescomponents of the inspection data selected in the above manner to make adetailed inspection such as classification on the inspection data.Reviewing or analyzing the date is performed manually or automaticallyand the results of classification are displayed and stored manually orautomatically. The results of classification analyzed by the analysisprocessing section 40 are stored as a group 41 c of analysis data.

An analysis data compiling section 50 performs an analysis datacompiling on two or more arbitrary data among the group 41 c of analysisdata. This section 50 adds the results of classification of the defects,such as categories, to the data 31 c after the identity judgment or apart of them.

The inspection data 51 c compiled by the analysis data compiling section50 are the summary of the above-mentioned inspection results of thesample 1 to be inspected. Desirably, the data of the above-mentionedinspection, the identity judgment, and the analysis are stored as theinspection data 51 c. Further, the analysis data compiling section 50feeds back the inspection data 51 c to the original group 11 ofinspection data to provide the inspection data of each inspectionapparatus in which the classification data are assigned to the sample tobe inspected.

In the manner described above, it is possible to analyze the differencebetween plural kinds of inspection apparatuses with respect to a sampleto be inspected, and further to perform plural kinds of inspections andanalyses with efficiency in a short time, as is the case with theabove-mentioned preferred embodiments (a), (b).

According to the preferred embodiments described above, the presentinvention can produce an effect of manufacturing a semiconductor deviceof high quality through a large number of manufacturing processes.

Also, according to the preferred embodiments described above, thepresent invention can produce an effect of inspecting particles to bedetected such as foreign particles under an optimal inspection conditionin accordance with the surface condition of a sample to be inspected,manufactured in various manufacturing processes.

Further, according to the preferred embodiments described above, thepresent invention can produce an effect of selecting a proper inspectionapparatus for a sample to be inspected, manufactured in variousmanufacturing processes.

The invention may be embodied in other specific forms without departingfrom the spirit or essential characteristics thereof. The presentembodiment is therefore to be considered in all respects as illustrativeand not restrictive, the scope of the invention being indicated by theappended claims rather than by the foregoing description and all changeswhich come within the meaning and range of equivalency of the claims aretherefore intended to be embraced therein.

1. A method of inspecting a sample, comprising the steps of: storinginspection data with position information on a sample which is obtainedby inspecting the sample under plural inspection conditions; checking anidentity of the stored inspection data to identify defect candidates bythe use of the stored position information on the sample; and displayingan image of said identity checked defect candidates in a map form on ascreen.
 2. The method according to claim 1, further comprising the stepsof: determining a defect candidate to be inspected in detail from theidentified defect candidates; and determining an inspection condition ofthe sample by use of information of an image of the defect candidatewhich is determined to be inspected in detail.
 3. The method accordingto claim 2, wherein said image used in the step of determining theinspection condition is obtained by reviewing the position on the sampledetermined to be reviewed.
 4. The method according to claim 3, whereinsaid reviewing is executed by using an optical inspection tool.
 5. Themethod according to claim 3, wherein said reviewing is executed by aninspection apparatus using a SEM.
 6. A method of inspecting a sample,comprising the steps of: storing position data of defect candidateswhich are detected under plural inspection conditions; comparing theposition data of each of the defect candidates detected under the pluralinspection conditions; judging identity of the defect candidatesdetected under the plural inspection conditions to reduce the defectcandidates to be reviewed by using information obtained at the step ofcomparing; and displaying said identity judged defect candidates on ascreen in a map form.
 7. The method according to claim 6, furthercomprising the steps of: determining a defect candidate to be inspectedin detail out of the identity judged defect candidates; and determiningan inspection condition of the sample by use of information of an imageof the defect candidate which is determined to be inspected in detail atthe step of determining a defect candidate to be inspected in detail. 8.The method according to claim 7, wherein said image used in the step ofdetermining the inspection condition is obtained by reviewing theposition on the sample determined to be reviewed.
 9. The methodaccording to claim 8, wherein said reviewing is executed by using anoptical inspection tool.
 10. The method of inspecting a sample as setforth in claim 8, wherein said reviewing is executed by an inspectionapparatus using a SEM.
 11. An apparatus for inspecting a sample,comprising: storing means for storing position data of defect candidateson a sample, which are obtained by an inspection apparatus bysequentially inspecting the sample under plural inspection conditions;checking means for checking identity of the defect candidates bycomparing the position data of the candidate which are stored in thestorage means; and display means for displaying on a screen saididentity checked defect candidates in a map form.
 12. The apparatusaccording to claim 11, further comprising: a defect candidatedetermining means for determining a defect candidate to be inspected indetail out of the identity judged defect candidates; and an inspectioncondition determining means for determining an inspection condition ofthe sample by use of information of an image of the defect candidatewhich is determined to be inspected in detail by the defect candidatedetermining means.
 13. The apparatus according to claim 12, wherein saidimage used by the inspection condition determining means is obtained byreviewing with a reviewing tool the defect candidate to be inspected indetail determined by the defect candidate determining means.
 14. Theapparatus according to claim 12, wherein said reviewing tool is anoptical inspection tool.
 15. The apparatus according to claim 12,wherein said reviewing tool is a SEM.